Accepted Papers

 Best Paper Awards

• VFGNN: A Mixed Framework for Vertically Federated Graph Neural Network
  Chaochao Chen, Fei Zheng, Jun Zhou, Lingjuan Lyu, Jianwei Yin, Longfei Zheng, Li Wang, Xiaolin Zheng

• Federated Node Classification over Graphs with Latent Link-type Heterogeneity
  Han Xie, Li Xiong, Carl Yang

 Oral/Spotlight Papers

• FedGCN: Convergence and Communication Tradeoffs in Federated Training of Graph Convolutional Networks
  Yuhang Yao, Carlee Joe-Wong

• Subgraph Federated Learning over Heterogeneous Graphs
  Ke Zhang, Han Xie, Zishan Gu, Xiaoxiao Li, Lichao Sun, Siu Ming Yiu, Yuan Yao, Carl Yang

• D^3RF: Distributionally Robust Federated Drug Discovery with Inter-client Noise
  Bingzhe Wu, Zhipeng Liang, Yuxuan Han, Yatao Bian, Peilin Zhao, Junzhou Huang, Chaochao Chen

• Federated Graph Machine Learning: A Survey of Concepts, Techniques, and Applications
  Xingbo Fu, Binchi Zhang, Yushun Dong, Chen Chen, Jundong Li

 Poster Papers

• Dynamic Activation of Clients and Parameters for Federated Learning over Heterogeneous Graphs
  Zishan Gu, Ke Zhang, Guangji Bai, Liang Chen, Liang Zhao, Carl Yang

• Graph Federated Learning with Hidden Representation Sharing
  Shuang Wu, Mingxuan Zhang, Yuantong Li, Carl Yang, Pan Li

• Federated Graph Representation Learning using Self-Supervision
  Susheel Suresh, Danny Godbout, Arko Mukherjee, Mayank Shrivastava, Jennifer Neville, Pan Li

• FedAA: Using Non-Sensitive Modality to Solve Non-IID Puzzles in Federated Learning
  Dong Chen, Siliang Tang, Carl Yang, Zijin Shen, Guoming Wang, Jun Xiao, Yueting Zhuang

• SplitGNN: Splitting GNN for Node Classification with Heterogeneous Attention
  Xiaolong Xu, Lingjuan Lyu, Yihong Dong, Yicheng Lu, Weiqiang Wang, Hong Jin

• FedGSL: Federated Graph Structure Learning for Local Subgraph Augmentation
  Yuxia Sun, Geng Zhao, Yi Huang